evo
A Python package for evaluating and comparing odometry and SLAM algorithm trajectories with support for multiple formats and metrics.
What is evo?
evo is a Python package designed for evaluating and comparing the trajectory outputs of odometry and SLAM algorithms. It provides metrics like absolute and relative pose error, supports multiple trajectory formats, and offers tools for visualization and analysis. It solves the problem of consistently benchmarking localization and mapping systems across different datasets and algorithms.
Robotics researchers, engineers, and students working on odometry, SLAM, or autonomous systems who need to quantitatively assess algorithm performance. It's also valuable for anyone comparing different SLAM implementations or validating their own against ground truth.
Developers choose evo for its comprehensive format support, flexible and configurable CLI, faster performance compared to other Python tools, and its modular design that allows for custom extensions. It provides a unified toolkit that avoids being locked into a single dataset's evaluation protocol.
Overview
Python package for the evaluation of odometry and SLAM
Use Cases
Best For
- Benchmarking SLAM algorithms like ORB-SLAM or S-PTAM against ground truth data
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